A digital image may contain one or more regions of interest (ROIs). In many applications, only image data contained within the one or more ROIs of a digital image may need to be retained for further processing and for information extraction by computers. Efficient and accurate identification of these ROIs thus constitutes a critical step in image processing applications, including but not limited to applications that handle high-volume and/or real-time digital images. Each ROI of a digital image may contain pixels forming patches with drastic variation in texture and pattern, making accurate and efficient identification of the boundary between these ROIs and the rest of the digital image a challenging task for a computer. In some imaging processing applications, an entire ROI or a subsection of an ROI may need to be further identified and classified. For example, in the field of computer-aided medical image analysis and diagnosis, an ROI in a medical image may correspond to a particular organ of a human body and the organ region of the image may need to be further processed to identify, e.g., lesions within the organ, and to determine the nature of the identified lesions.